SOCIAL NETWORK BASED RECOMMENDATION METHOD AND SYSTEM

Recommendations for content may be generated based on social networking communities. For example, a user may receive a list of recommended content items based on content that has been viewed by others in the user's social networks. Recommendations may further be based on content information such as reviews, ratings, tags, attributes and the like from various sources internal and external to the user's social networks. Content items may be given a weight that corresponds to a determined level of relevance or interest to a user. Using the weight, a list of recommended items may be sorted or filtered. In one or more configurations, the weight may be modified based on an age of the content item. For example, the relevance, importance or interest of a news report may decline as the news becomes older and older.